Population
Forecasting Methods: A Report on Forecasting and Estimating Methods

Part II: Current Techniques of Forecasting

Several general methods for making population projections for areas and
communities are in common use. Under each of these general methods, a variety
of procedures and techniques has been developed. Those most followed in
practice will be briefly reviewed. The general methods are:

Graphical or mathematical projections of the curve of past population
growth (trend based methods).

Projections based on relationships of population growth in an area to that
in other areas (ratio methods).

Projections of net migration and of natural increase (component methods).

Forecasts based on specific estimates of future employment and other
occasionally used methods.

It must be emphasized that in practice few studies will use one method in
the manner described in this report. Often a particular area will have
conditions which will best be met by adopting a unique method. Often, the
background of the staff may lead them to change methods to achieve what they
believe are better results. For example, the projections presented in the St.
Paul, Minnesota, Community Plan Report No. 12 are based on empirical data from
other studies. The Army engineers, faced with a need for forecasts to the year
2020 in the San Francisco Bay Area, adopted a ratio technique combined with
considerable judgment and modifications.

Method I - Graphical or Mathematical Projection of the Curve of Past
Population Growth (Trend Based Methods)

The trend based methods assume that population growth follows natural laws
and, therefore, can be expressed in mathematical or graphical form. Basically,
population is forecast by examining and projecting past trends into the future.
Various types of expressions have been used such as linear, geometric,
exponential, logarithmic, etc., to explain past historical growth and predict
future growth. Usually, no analysis is made of factors that cause population
changes, e.g., births, deaths, and migration.

Trend Based Projections by Graphic Techniques

Graphic projections are most commonly made using arithmetic, semilog, or
probability paper. The data used in the plotting are historic data from
decennial census reports and from available local or State census reports from
intermediate years. The historic data are often plotted on all three types of
graph paper, and the plot which comes closest to a straight line indicates the
mathematical form to be used for the projection. In using the plotted
information for projection purposes, the analyst assumes that the condition
implied by the straight line will continue into the future.

(1) Constant arithmetic population increase

Historic data which plot as a straight line on arithmetic graph paper imply
constant arithmetic change in population each year. This growth pattern implies
that the population has changed by the same number of people each year. The
data from Table 1 would appear as a straight line when
plotted on arithmetic paper as shown in Figure 1. Since
the base population each year has increased (or decreased) by a constant
amount, the rate of change is different each year.

(2) Constant rate of population increase

A different historic growth pattern for a city might show a constant rate of
change. When the data shown in Table 2 are plotted on
arithmetic graph paper, such a pattern of growth forms a curve as shown in
Figure 2. When the same data are plotted on semilog paper
(with population on the log scale and time on the arithmetic scale), a straight
line plot results as shown in Figure 3. In this situation,
the numerical increase each year is greater than the year before, although the
rate of increase is constant.

(3) Variable rate of population change

Arithmetic plots for some cities have shown that at first the population
increased at a low rate, then accelerated for a period of time, and later, as
the city matures, the rate of growth decreased. When the data in
Table 3 are plotted on arithmetic paper, such a condition
results in the characteristic "S" shade curve shown in Figure 4. These same data may be plotted on probability paper
resulting in a straight line as shown in Figure 5. This
curve is known as the logistic curve.

The logistic curve is based on a "law of growth in a limited area"
propounded and mathematically developed by P. F. Verhulst in 1838. It is shaped
like an elongated and flattened letter "S." The curve was
rediscovered independently many years later by Messrs. Raymond Pearl and Lowell
J. Reed from observation of the growth of fruit flies contained in glass jars
and subjected to controlled conditions of food consumption.

It was found that in the early stages the increase in the number of fruit
flies per unit of time accelerated to a maximum, after which it decreased at a
continuously decelerating rate per unit of time, inverse to the previous
growth. Some population analysts believe that what happens to the growth of
fruit flies in a jar would apply to the human population of a completely
self-contained area.

In fact, several population forecasts made a few decades ago indicated an
upper limit to the population of the United States would be reached before
1990. The validity of this "law" for areas subject to net immigration
that might accelerate for a time is questionable.

Trend Based Projections by Mathematical Techniques

The mathematical technique for projecting population also utilizes historic
data and produces results similar to those obtained through the graphical
techniques. In their simplest form, mathematical techniques are nothing more
than the equations that will reproduce a straight or curved line. The basic
theory for this is that any smooth line which can be plotted can be expressed
(or at least approximated) by an equation.

A somewhat more advanced method is to derive the equation for the line which
best fits the historic points and use this equation to estimate future
population. Normally, the method of least squares would be used to obtain the
equation of this line. Occasionally multivariate equations or equations using
terms expressed to a power are utilized. Some of the factors included in these
equations have been economic changes, land available, historic inter- and intra
area population movements, etc. There is no standard group of variables
employed in these equations, however, and in most cases the mathematical and
graphic techniques have been used for very specific small area projections of
only certain sectors of the population such as the number of home owners, or
children in school.

Modified Projections

Forecasters often modify or alter projections arrived at by the previously
described mathematical and graphic techniques according to their ideas about
how the projected curve should look. In fact, given the same data of past
growth, a dozen forecasters probably would come out with somewhat different
graphic or mathematical projections. It is often difficult to determine by eye
the graphic projection that would exactly fit the curve. Likewise, in computing
the mathematical equation for projecting the curve, there might be differences
in the number of points that would be considered or differences in the starting
points.

In addition, forecasters often raise or lower their projections they have a
hunch that the future population will be larger or smaller than the projected
figure. Such subjective modifications are usually hazardous , and they are not
recommended. Modifications should be made after a thorough study of influences
end conditions affecting rate of population change in the area.

It is suggested, however, that projections obtained by other methods
described later be plotted along with the curve of past growth. If the
Projections thus plotted appear to differ sharply from the previous curve,
careful review of the analysis should be made to catch any error in the
evaluations or computations.

Critique

The advantage of graphic or mathematical projections is that they are the
easiest to make. They generally are better suited to areas which have had
relatively constant changes per decade in the size of their populations and for
which no marked changes from past trends appear likely, than for areas subject
to rapid or erratic fluctuations in population. Obviously, they should be more
dependable for short-term projections of 5 to 10 years, than for longer
projections.

The weakness of such projections is that they are founded on the assumption
that the factors and conditions which produced population growth or decline in
the area in the past will continue unchanged and will have the same effects in
the future, or that they are derived from an assumed curve of population
growth. In view of the changes that have taken place during the past two
decades in fertility, mortality, and migration trends, projections of this kind
are becoming less reliable. Graphic and mathematical projections are useful,
however, as rough checks on those obtained by other methods.

Method II - Projections Based on Relationships of Population Growth in an
Area to Growth in Other Areas (Ratio Methods)

The factors and influences that accelerate or retard natural population
increase are pervasive and tend to speed it up or slow it down concurrently
throughout the Nation. Moreover, as mentioned before, economic and social
conditions that cause birth rates to rise, or decline, also tend to accelerate
or decelerate internal migration. Because of this, the rate of population
growth in most areas and communities is related to some extent to the growth
rate of the national population.

Population growth in an area or community is usually closely related to, or
affected by., economic and population changes in the economic region or State
in which it lies. Future population changes in those larger areas may have an
important influence on growth or decline in the smaller area. Hence, past
relationships between population growth in an area or community and that of its
economic region or State are valuable guides for projection of the local
population. If logically founded population projections for the Nation, State,
or economic region are available, projections for the area or community can be
derived directly therefrom. National projections are available in the Current
Population Reports, Series P-25 published by the Bureau of the Census (see
Appendix II, Data Sources).

Statistical Projections Based on Relative Rates of Past Growth

The population growth of a study area can be projected into the future by
relating its growth to a larger area of which it is a part, such as the State,
the region,, or the Nation. The basic procedure is to compute the ratio between
the population of the study area and some larger area at the time of past
censuses. This ratio may simply be between the study area and a larger area, or
a series of interrelated ratios may be calculated between pairs of successively
smaller geographical areas. Such a series, known as step-down ratios, might be
between the study area and the State economic area, the State economic area and
the whole State, the State and the region and, finally, the region and the
Nation. The availability of a reliable forecast for a larger area and
comparable historic data for the subareas to be used should be examined before
this method is selected.

The historic ratios developed must then be plotted in a time series and
projected forward. Their projection is not a simple mechanical procedure, but
involves taking into account all the factors discussed in part of this report.
Local conditions must be examined and the probable factors which will influence
the future ratios fully understood. Simply because a ratio has had a particular
trend in the past is no assurance that it will continue to have that
relationship in the future. For example, during the early decades of this
century., coal mining towns in the Appalachian area grew at a faster rate than
their State as a whole. However, during the past few decades, this trend has
been reversed.(6)

Example of the Ratio Method

To illustrate the procedure used in the ratio method, a sample projection
for the years 1970 and 1980 will be made of the population of a hypothetical
study area by projecting the historic ratio with the State.

The first step is to list the historic population data for the study area
and the State in order to derive the necessary historic rates. The type of
information required, as shown in Table 4, may be obtained
from census data.

In developing the ratios, care must be taken to see that the geographic
boundaries of the area used in each census year are the same as for each of the
other years. Thus, if a four-city area is the study area in 1960, the same
geographic area of the four cities must be used in the time series.

The next step is to obtain State population forecasts for the years 1970 and
1980. These could be obtained by stepping down from the national forecasts
prepared by the U.S. Bureau of the Census or some other agency. In this
example, it will be assumed that a State agency has prepared population
forecasts. The forecasted figures are 2,500,000 persons in 1970 and 3,200,000
in 1980.

In addition to obtaining the population forecast for the State, it is
necessary to prepare ratios of the study area population to State population
for the years 1970 and 1980. The preparation of these ratios is the most
important part of this forecasting technique. All of the factors which
influence population change as discussed in part I must be considered and
analyzer as to their probable future effect on the study area's share of the
future State population. In this example the study area share in the total
State copulation has been increasing. Assuming that a study of births, deaths,
migration, employment, and economic trends indicate a continuation of an
increasing ratio, although at a declining rate, then the forecast ratios of
0.124 for 1970 and 0.126 in 1980 can be considered reasonable. With this
information, the study area population can be forecast for 1970 and 1980 as
shown in Table 5.

Critique

Purely statistical projections made by ratio methods should be used with
caution. Former relationships between population growth in the area under
consideration and that in other areas may suddenly change. Moreover, the
economic and social forces that cause births and migration to increase, or
decline, nationally exert differing effects at different times on particular
areas. Some areas have shown fairly consistent trends between their population
growth and that of their region, State, or the Nation. Others have shown
divergent or erratic relationships to population changes in the larger areas.
For these this method appears less valid than for areas exhibiting more
consistent trends.

The ratio method, based upon a forecast for a large area, is subject to all
the errors, incorrect assumptions, and inaccuracies inherent in that forecast.

Very often local forecasters are not aware of all the assumptions made in
preparing the larger base area figures. Moreover, there is no assurance that
the assumptions made would have the same effect on the study area as they would
have on the larger base area. It is quite possible that the growth in the
economy which is assumed in a national forecast would imply a change in
technology. This change might force the basic economic activities in the study
area to make radical reductions in employment or move to new areas. (Examples
of such situations are the Appalachian coal mining companies and the New
England textile mills.) Even on the State level., a forecast of continued
population growth in a particular State does not necessarily imply an even
distribution of growth within the State. It might also mean a large growth in
one or two urban areas with little or no growth (or even out-migration) in
other urban areas within the State.

On the other hand, these procedures have several advantages over trend
methods. The factors affecting population growth in the area or community may
be more clearly visualized and appraised with a knowledge of its past
relationships to growth in its economic region, State, and the Nation than if
these relationships have not been studied. It may be easier to foresee and
evaluate the effects of new conditions that may change past relationships than
it would be to appraise the prospects for future growth in tile area
irrespective of the rate of growth in other areas. Population projections for
the Nation and for States have generally been closer to the mark than those for
smaller areas or communities. By tying in their projection with those for the
larger area, the range for error may be lessened.

Several recent transportation studies have used ratio techniques; among them
Niagara Frontier, Billings, Montana, and Champaign-Urbana, Illinois. In the
Puget Sound area, both the Regional Planning Council and the regional
transportation study have used ratio techniques in preparing population
forecasts.

Component analysis methods study separately several factors, such as births,
deaths, and migration which affect the future size of population. The theory
behind component analysis is that more accurate estimates can be made using the
rates of change of the individual components of population than can be made
using the rates of change for the population as a whole. For example, it is
reasonable to assume that birth, death, and migration rates for 80-year old
people are different than those for 20 year old people and that, based on
historic experience, one can forecast the rates for such groups with reasonable
accuracy. This discussion will concentrate on the two most common component
methods: First, the natural increase and net migration methods, and then cohort
survival and net migration methods. Because migration is common to both
methods, and forecasts of net migration are usually made before those for the
natural increase, migration projections will be discussed first.

Migration Projections

Logically founded projections of net migration can be developed from study
of net migration in the area in the past and the conditions causing people to
move into or out of it.

The direction and approximate volume and composition of net migration into
or out of the area during recent decades are first determined. The influences
that have induced the population movements., especially economic factors, are
next investigated. The economic factors themselves are part of the economic
study phase of the transportation planning process and the population
forecaster should work closely with the economists in understanding these
relationships. Analysis of the physical and economic resources and
characteristics of the area, the trends and rate of its development, and other
factors will usually reveal the principal causes. Factors affecting migration
have been briefly reviewed in part I. Past relationships between net migration
in an area and population growth in its economic region, State., and the Nation
provide further guides for the projections.

Changes that occurred, or appear likely to occur, in the conditions and
relationships affecting migration in the area are then considered. Finally, the
probable effects of such changes on net migration during the forecast period
are reviewed and appraised.

With these analyses and appraisals, it is usually possible to develop
reasonable high and low projections for net migration. At least, they provide
some indication whether net migration during the next decade may be expected to
be about the same as, or larger or smaller than) that of the preceding
decade.

Estimates of future net migration in substate areas also have been made by
analyzing the trends of geographical distribution of net migration into the
State in recent decades and projecting these trends.(7)

Natural Increase Projections

In the natural increase methods., the population is treated as a whole or as
a few major groups and appropriate growth rates which reflect the net effects
of births and deaths are applied to each group. For areas having substantial
portions of nonwhite residents, historic trends should be analyzed and
projections made separately. If natural increase is expected to be the
principal source of growth, then this component of population change assumes
greater importance and should be examined in greater depth. The natural
increase rates to be used for projection are derived by study and analysis of
the factors which influence births and deaths as discussed in part I of this report. The projected rates are then applied
to the base period population to arrive at the population growth due to natural
increase.

Migration and Natural Increase Methods

As an illustration of the natural increase and net migration method, another
hypothetical city having the characteristics shown in Tables
6 and 7 and 8 will be used.

Cohort-Survival and Net Migration Methods

The other component method which will be discussed here is the
cohort-survival and net migration method. A cohort in a population analysis is
defined as a group of people with a common set of characteristics who were born
during the same tire period. An example of a cohort would be all males born in
January 1, 1915, through December 31, 1944, (this group would have been 15-44
year old male group in 1960), or all females, white born from January 1, 1940.,
through December 31. 1944.

Note that any specific age grouping (say 20-24 years of age) refers to any
particular cohort at only one period in time. At the next period all the living
members of the cohort will be in the next higher age group (in this case the
group 25-29 years of age), but they will still be members of the same cohort
(i.e., those born during the same time period).

There are no set of rules for defining the detailed breakdown of cohorts but
a commonly used procedure in planning studies is to divide the population into
five-year cohorts with two five-year intervals corresponding to one 10-year U.
S. Census period. The five-year cohorts are then usually subdivided into male
and female and where nonwhite population is of significant size, the age-sex
groupings are further subdivided into white and nonwhite.

The future population is forecast by taking each of these age-sex groups and
aging them through one of the forecast intervals. Assuming this period to be
five years in length, this means that each cohort will move to the age group
five years older. During this period some members of each cohort can be
expected to die. Deaths are forecast by using annual death rates for each
age-sex group multiplied by the forecast interval to obtain total forecast
deaths for the interval. The survivors, who will become the new age group five
years later, are forecast by subtracting anticipated deaths from the size of
the cohort at the start of the forecast period.

The total net migration projected for the area to the forecast date is then
distributed by sex and by age, and added to, or subtracted from, the figures
for the surviving residents in the corresponding age groups. It should be noted
that the sex and age characteristics of the migrant population are usually
quite different from those of the resident populations of the areas from which
they move or in which they settle. The sex and age distribution of net
migrations into or out of the particular area or its State during recent
decades, therefore, should be carefully analyzed and used as guides in
estimating the sex and age distribution of the projected net migration.

Birth rates by age of mother during the forecast period are then projected
or assumed. The expected number of births is then obtained by multiplying the
assumed age-specific birth rates by the average number of women in each
five-year age group within the child-bearing ages during the forecast period.
This average figure is usually obtained by adding the number of women at the
beginning and end of the forecast period in each five-year age group, and
dividing by two. The survivors of those births on the forecast date are then
computed by using death rates of young children. As the number of male births
usually exceeds the number of female births in the ratio of about 105 or 106 to
l00, this should be taken into account in precise calculations.(8)

The cohort-survival procedure does not directly measure natural increase
itself. Instead, the population projection is obtained by-adding the survivors
of the resident population., the expected net migration., and the survivors of
babies born to residents and to newcomers during the period. If the net
migration is outward, the estimate of births is reduced because of the smaller
average number of women in the child-bearing ages. Since most of the adult
migrants are between ages 20-45 years,. when they move, net out-migration tends
to reduce the crude birth rate also. Further refinements, such as allowances
for births to in-migrant women who the during the period, are sometimes
included in the calculations.

As an illustration of the cohort-survival technique, a population forecast
will be made for one cohort in a hypothetical city. The cohort will be all
those women born during the period January 1, 1935, through December 31, 1939.
These are the women who were 20 through 24 years of age on January 1, 1960. It
will be assumed that in the 1960 Census of Population., there were exactly
2,000 women in this age group.

The cohort-survival method requires as input the expected number of migrants
in each age-sex group for each forecast period. This forecast is usually
prepared by first forecasting the total migrants and then distributing them to
the age-sex groups. The distribution into age-sex groups must recognize the
different characteristics of migrants and residents. Often the historic ratios
between the age-sex groups of migrants are used directly for this purpose.

To illustrate this method of distributing migrants into age-sex groups,, the
anticipated number of women migrants for this cohort in 1965 and 1970 will be
calculated. Historic ratios are calculated based on migration
information obtained from the 1960 census which contains information on
1955 to 1960 migration. Table 9 shows ratios derived from
census data for the study area.

It will be assumed that for this example the forecast net migration into the
study area is 4,000 for the period January 1, 1960, to January 1, 1965., and
5,000 for the period January, 1, 1965, to January 1, 1970. The migrants will be
added in as a group at the beginning of each five-year time period.

The allocation of these migrants to age-sex groupings now becomes a simple
process of using the historic ratios (or changing them if a study indicates
that a change is to be expected) in conjunction with the total migration
figure. In the following illustration it will be assumed that the ratios are
satisfactory so they will be used unchanged. The allocations to the sample
cohort of women will be:

Total net immigration 1960-1964

Ratio immigrants who are women age 25-29

Number of women migrants age 25-29 January 1, 1965

4,000

X

0.049

=

196

Total net immigration 1965-1969

Ratio immigrants who are women age 30-34

Number of women migrants age 30-34 January 1, 1970

5,000

X

0.045

=

225

The natural increase part of the cohort-survival method consists of
estimating deaths occurring among members of each cohort during each iteration
period and subtracting these deaths from the membership of each cohort. Death
rates can be obtained from one of the sources described in the section on
sources of data. The death rate in the study area for women age 20 through 24
will be assumed to be 2.4 deaths per year per 1,000 women. Thus, in the case of
this cohort the following calculations would be made:

No. of Members in cohort women age 20-24

Annual death rate per 1,000 women age 20-24

No. of years in interation period

Anticipated deaths per five-year interation period

2,000

X

2.4

X

5

=24

1000

These deaths are subtracted from the members in the cohort at the beginning
of the iteration period to determine survivors at the end of the period. (2000
- 24=1976).

These survivors are now members of the 25 through 29 year age cohort in
1965. The full cohort in 1965 will consist of these survivors plus or minus
migrants. In this example we have already calculated 196 women
immigrants in this age group during this time period. Thus, the total
membership of the cohort women born January 1, 1935, through December 31.,
1939., is estimated to be: (1976 + 196=2172).

This total cohort is now in the 25-29 year age group in 1965, and may now be
moved forward another five years by the same procedure. For example, assume
that the projected death rate for women 25 through 29 years of age is 2.8
deaths per year per 1,000 women. The estimated deaths would then be calculated
by multiplying the rates by the number of years in the iteration period.

2.8

(2172 X l000 x 5=30)

The forecast number of women immigrants in this cohort during this five-year
period was calculated as 225. Thus, on January 1, 1970, the forecasted
population of women age 30 through 34 is: (2172 - 30 + 225=2367).

Note that the group illustrated is one cohort. That is, they were all born
during the same time period and have common characteristics as they were
previously defined. During each time period some of the original members are
lost through deaths and new individuals migrate into the area and are added to
the cohort. (The migration could be negative in which case the cohort would
lose members.) The survivors and migrants are then moved to the next older age
group. Note also that an identical table format would be prepared for males in
the study area.

Births are handled as a separate set of calculations in cohort survival
analysis. The local birth rates for each age group of women are obtained from
vital statistics and these rates are then applied to the number of women in
each age group. Since most children are born to women in the 15-44 year age
range, the rates are usually prepared and applied only to these groups.

As an illustration., it will be assumed that the birth rates in the study
area are found to be 239.6 births per year per 1,000 women in the 20 through 24
year age range. Applying the proper rate to women in the 20-24 year age range,
the following calculations are made:

Av. No. women age 20-24 alive during 5-year period

Ann. birth rate women age 20-24 (per 1,000 women)

No. of years in iteration period

No. of births to women age 20-24 during iteration period

2,000 1,976

X

239.6

X

5

=2,380

2

1,000

Similarly the number of births occurring in the study area to women who move
into the area may be calculated by assuming that they live here one half of the
time. (Such an assumption would assume an equal number of migrants would arrive
each year during the five-year period.) Thus, the formerly assumed rate of
4,000 migrants from 1960-65 implies that 800 arrive each year. As noted
earlier, 204 of the 4,000 migrants have been assumed to be in the 20-24 year
age group. The following calculations are made:

No. of female migrants age 20-24 during 5-year period

Ann. birth rate women age 20-24 (per 1,000 women)

One-half No. years in iteration period

No. of births to migrant women age 20-24 during iteration period occurring
in study area

204

X

239.6

X

2.5

=122

1,000

The estimated births to women in this age group are added to the births
estimated for women in other age groups in the child-bearing range to determine
the children born in the study area to be assigned to the 0-4 year age group in
the next iterative period. Breakdowns by sex are obtained by studying past
ratios of males to females among local births. To these children must be added
children of migrants who were born elsewhere during this time period and
brought into the study area by their parents (or who left with their parents if
the local area is undergoing out-migration).

Critique

The component method is being relied on more and more for population
projections. For most areas and cities, it should yield better forecasts than
trend and ratio methods, particularly for projections not exceeding two
decades.

Component methods take into account the size of the area's population at the
beginning of the forecast period, and the effects of a population of that size
on future births, deaths, and migration. Trend and ratio methods do not provide
as accurate measures of the effects of changes in the size of the population
from decade to decade.

Moreover, this method requires the forecaster to appraise the effects of
various influences on each of the three sources of population change instead of
making a less discriminate evaluation of their effects on population growth as
a whole. Certain influences, such as rapid economic development, may accelerate
migration into an area but have relatively little effect on its birth and death
rates. This method also measures the reaction of migration on natural increase
instead of blanketing this quantitative effect in with a host of qualitative
considerations.

The range of future birth and death rates usually can be determined with a
smaller margin of error than that of future migration. Component methods are
therefore especially useful for projections in which natural increase is
expected to be the principal source of population growth. Hence, it is almost
invariably used for projections of the national population.

If the population information is needed for a special purpose for example,
anticipated school enrollment or licensed drivers - the cohort-survival method
will provide this information without the need for additional calculations. In
addition, the method is highly recommended for areas which have a population
distribution which differs radically from that in the rest of the region (e.g.,
an area which has a large number of elderly residents).

Approximate projections of natural increase) assuming no migration in the
area, can be made easily and quickly. These will give a good indication of
minimum growth to the forecast date, unless there is a net out-movement, and
are valuable checks on projections made by other methods.

It is also easy, once the initial data have been gathered, to prepare more
than one forecast based upon different assumptions as to births, deaths, and
migration. Such alternative series are especially of value in understanding the
implications of some change which will affect one of these components (as for
example, a road system which would encourage growth of economic activities
which would attract heavy immigration).

Component methods have been used by several studies; among them the
Penn-Jersey Transportation Study, the Portland, Oregon, Metropolitan Planning
Commission, the Salt Lake Area Transportation Study, and the Dade County
Planning Department. The Luzerne County, Pennsylvania, (Wikles - Barre -
Hazleton area) Planning Commission used this method for the forecast and then
used a ratio method as a check on the reasonableness of the projected figures.

Method IV - Forecasts Derived Directly from Specific Estimates of
Employment and Other Occasionally Used Methods

The three methods already discussed; trend based, ratio, and component, are
the most prevalent methods of forecasting population. Several other methods
have also been used enough to warrant a brief discussion of them. Three of
these methods will be discussed here; first, forecasts based on economic
projections; second, comparative or analogy methods; and third, the holding
capacity method. The last two methods are not considered satisfactory for large
area forecasts and would best be avoided for transportation study purposes.

Population forecasts based on future labor force estimates

The ability of any area to grow in population depends to a great extent upon
its ability to support this population with jobs. Thus, a forecast of the labor
force(9) available from an economic study as a
part of the urban transportation planning-process can form the basis for a
population forecast. When so developed, this population forecast can be used to
check the population forecast arrived at by demographic methods (i.e., using
mathematical, graphical, or other type of projections of past relationships in
which the effects of economic factors on population change are implied but not
expressly stated or studied in detail).

The translation of a labor force forecast into a population forecast is
accomplished by using the projected labor force-to-population ratio. (This is
called the "labor force participation rate.")(10) Before undertaking to project it into the
future a study should be made of past trends to gain an understanding of the
factors that have influenced this rate in the past and which may affect it in
the future; for example, the delayed entrance into the labor market of young
people continuing their education and the increasing participation in the labor
force of married women after their children are grown. Additionally, the early
retirement of older workers may be an important element affecting this rate in
a particular area, depending upon the characteristics of the population and the
hiring practices of the firms in that area.

The population forecast is prepared by applying the projected labor force
participation rate to the labor force forecast and making adjustments as
necessary to account for the military and/or the institutionalized population.
To illustrate, the following tabulation shows historical data on the total
civilian population, the civilian labor force, and the labor force
participation rates for an assumed study area.

Year

Total Civilian Population

Civilian Labor Force

Labor Force Participation Rate (Col. 3/col. 2)

1930

100,000

39,700

39.7%

1940

120,000

48,200

40.2%

1950

145,000

62,200

42.9%

1960

185,000

75,900

41.0%

Using the forecast of the total civilian labor force prepared by the
economic study and applying the forecasted labor force participation rates
(i.e., dividing the labor force by the rate and multiplying by 100), the
civilian population can be computed as shown in the following tabulation.

Year

Forecast Civilian Labor Force

Forecast Labor Force Participation Rate

Labor Force Civilian Population

1965

31,600

40.8%

200,000

1970

87,100

40.5%

215,100

1975

94,500

40.2%

235,300

1980

102,000

40.0%

255,000

If the labor force figures are broken down by types Of jobs and
characteristics of workers, it is possible to prepare more detailed estimates
of population by age, sex, and race.

Critique

This method assumes that the volume of employment in an area on a future
date can be forecast from consideration of certain economic factors alone,
without taking into account the probable size of the future population. It
implies that the volume of future employment can be forecast with greater
accuracy without reference to the size of the future population than the size
of the population can be forecast without having a specific forecast of the
future employment level.

The relationship between economic expansion and population growth in an
area, however, is somewhat like that of the chicken and the egg. Development of
extractive or commodity producing industries, a new irrigation project or a
large -new factory, normally will create new jobs. But people also move into an
area for a variety of other reasons (e.g., health or retirement) and such
in-migration itself tends to expand employment.

In most areas, the future employment level will not be determined solely by
the rate of expansion or decline of the so-called "basic" industries.
It will also be affected by the rate of population growth in the area, and by
changes in transportation, trade, and service activities, and government
employment,. Which may be unrelated to local production of tangible goods.
Moreover, the rates of expansion in local agriculture, manufacturing, and
construction themselves may be influenced by such changes. This is particularly
true of areas receiving continuous immigration, such as those on the Pacific
Coast.

Furthermore, the proportion of the population in the employable ages and the
ratio of labor force to population may also differ over time from the assumed
ratios. It would therefore seem unwise to rely solely on population forecasts
made by this method.

On the other hand, the analyses and evaluations of prospects for increase or
decline of economic activities provide valuable information which is useful in
making projections of net migration and natural increase by component methods.
They can especially aid the forecaster in determining net migration during the
forecast period would likely be in the same direction. and in higher or lower
amount, than in the preceding decade.

Comparative or analogy method (not recommended)

This method assumes that if two areas have similar characteristics such as
geography, climate, economic potential, culture, natural resources, etc., their
growth patterns will be similar. In practice the forecaster chooses a city
which has these similar characteristics and is already further developed than
his study area. He then projects the future growth of his study area as similar
to the past growth of the developed area.

The simplest projection method is to choose a developed area with similar
characteristics whose early population, growth curve is similar to the past
growth curve of the study area: that is, the population growth curve for the
developed area from 1850 to 1900 might be parallel to the growth curve for the
study area from 1940 to 1960. An assumption is then made that the part of the
curve being projected beyond 1960 for the study area will parallel the historic
curve for the developed area following 1900. Such a situation is shown in
Figure 6. Note that the population size for the two areas is
not necessarily equal nor need the time scales (the X axis) be identical.

A more complex method of making a comparative forecast is to study several
developed areas, each of which has at least one or two similar characteristics
in common with the study area. The differences and similarities between the
study area and each of the developed areas are examined and an average
population curve is developed from the several curves analyzed. This
"cumulative" curve then becomes the population growth that is used in
projecting the total population in the study area.

Critique

As a method of projecting population for a metropolitan area the comparative
forecast analogy method has severe weaknesses. It is doubtful that there are
two urban areas that are sufficiently alike to be able to say that the second
will grow in a similar manner to the first. Moreover, even if one could assume
that they were identical, it is still doubtful that two areas developing at
different periods in history would follow the same patterns of growth.

The comparative or analogy method may still have same value in forecasting
population for small areas. A good example would be in out-lying areas of a
metropolitan community where urban development and population growth in a
currently open area may be anticipated to follow that of a similar, but already
developed area. When used in conjunction with such factors as zoning, holding
capacity, accessibility, available utilities, etc., this procedure may give a
reasonable indication of the small area patterns which might occur.

Holding capacity method (not recommended)

This procedure assumes that an upper population density limit can be
established for an area, and therefore an upper limit to the number of people
who live in that area can be established. The maximum. population capacity is
derived through studies of zoning, land characteristics, available water, and
other land use measures. The population is then -assumed to grow until it fills
all or a certain percentage of this capacity.

Critique

Since the holding capacity of any metropolitan area is likely to be much
larger than any realistic population size that will live in the area, the
method requires the forecaster to assume some percentage of the capacity which
will be filled. This in effect results in subjective decisions by the
forecaster. Moreover, holding capacity is not a constant. Areas currently zoned
for low density may be changed to density when the demand arises. For small
area analysis within an urban area, the method may have more validity but it
becomes less reliable When used for the total metropolitan study area.

An example of a study using this method is the Seattle, 98 Washington, City
Planning Commission forecast by census tracts to 1985. It is important to note
that this forecast is for a closed area, the city of Seattle, and not for the
total area which would have to be included in the transportation study.

Endnotes

6. For a discussion of a method of projecting ratios,
see: U. S. Bureau of the Census, Current Population Reports,
"Population Estimates," Series P -25, No. 110, February 20, 1955.

7. Considerable data on migration in local areas are
available from the 1960 census of Population. A report of special interest is:
U.S. Bureau of the Census, "Components of Population Change, 1950 to
1960,, for Counties, Standard Metropolitan Statistical Areas, State Economic
Areas, and Economic Subregions," Current Population Reports, Series
P-23,, No. 7., November 1962.

8. Many areas will find that a completely update
forecast may be obtained by the simple use of birth rates for all women aged
15-44 and the number of women in this age group rather than perform the
individual calculations for each five-year age group.

9. The U.S. Department of Labor defines the labor force
as the noninstitutional population, 14 years of age and older, working or
looking for work. Thus, those classified as employed plus those classified as
unemployed constitute the labor, force. The total force includes the
armed forces. The civilian labor force excludes the armed forces.

10. The labor force participation rate (or ratio) may
be expressed in various ways. For example, the labor force figure may or may
not include the military. The denominator of this ratio may also vary by
including or excluding persons under 14 years of age. The national labor force
participation rate relating the total labor force to total noninstitutionalized
population varies around 41 percent (give or take 5 percent). But the rate for
the nation that relates the total labor force to the population 14 years of
age or older, varies around the 55 percent figure.

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